标题： 可扩展的走走停停波分析 显示英文标题

标题： Scalable analysis of stop-and-go waves

摘要： 分析以英里和小时为单位的数据中的停车-启动波是一项新兴的交通研究挑战。在过去，数据集规模有限，可以通过手动或基本方法轻松分析，以识别数据中存在的非常有限的一组交通波。本文介绍了一种自动且可扩展的停车-启动波识别方法，能够捕捉波的生成、传播、消散以及分支和合并现象，这些现象之前很少被观察到。通过基于临界速度的简洁且简单的停车-启动波定义，所提出的方法识别了所有波边界，这些边界涵盖了车辆速度低于选定临界速度的空间-时间点。该方法基于与停车-启动波相关的空间-时间点（特别是波前起点和波尾终点）的图表示，并将问题视为图组件识别问题。该方法用Python实现，并在大规模数据集I-24 MOTION INCEPTION上进行了演示。从这次演示中揭示的新见解包括：(a) 我们证明了波在从未见过的尺度（英里和小时）和普遍性下生成、传播和消散；(b) 波前和波尾在10-20英里/小时的临界速度下以一致的速度传播，跨车道传播存在差异，外侧车道的波速比内侧车道的波速更不稳定；(c) 波前和波尾以不同的速度传播；(d) 波边界捕获了丰富且非平凡的波拓扑结构，突显了波的复杂性。 显示英文摘要

摘要： Analyzing stop-and-go waves at the scale of miles and hours of data is an emerging challenge in traffic research. In the past, datasets were of limited scale and could be easily analyzed by hand or with rudimentary methods to identify a very limited set of traffic waves present within the data. This paper introduces an automatic and scalable stop-and-go wave identification method capable of capturing wave generation, propagation, dissipation, as well as bifurcation and merging, which have previously been observed only very rarely. Using a concise and simple critical-speed based definition of a stop-and-go wave, the proposed method identifies all wave boundaries that encompass spatio-temporal points where vehicle speed is below a chosen critical speed. The method is built upon a graph-based representation of the spatio-temporal points associated with stop-and-go waves, specifically wave front (start) points and wave tail (end) points, and approaches the solution as a graph component identification problem. The method is implemented in Python and demonstrated on a large-scale dataset, I-24 MOTION INCEPTION. New insights revealed from this demonstration with emerging phenomena include: (a) we demonstrate that waves do generate, propagate, and dissipate at a scale (miles and hours) and ubiquity never observed before; (b) wave fronts and tails travels at a consistent speed for a critical speed between 10-20 mph, with propagation variation across lanes, where wave speed on the outer lane are less consistent compared to those on the inner lane; (c) wave fronts and tails propagate at different speeds; (d) wave boundaries capture rich and non-trivial wave topologies, highlighting the complexity of waves.